Effect of chamfer width and chamfer angle on tool wear in slot milling

The tool geometry is generally of great significance in metal cutting performance. The response surface method was used to optimize chamfer geometry to achieve reliable and minimum tool wear in slot milling. Models were developed for edge chipping, rake wear, and flank wear. The adequacy of the models was verified using analysis of variance at a 95% confidence level. Each response was optimized individually, and the multiple responses were optimized simultaneously using the desirability function approach. The Monte Carlo simulation method was applied to tolerance analysis. All milling tests were conducted at dry conditions; the chamfer width and the chamfer angle varied between 0.1 and 0.3 mm, and 10 and 30°, respectively. Optimal chamfer geometry for minimizing chipping and rake wear was small chamfer width and chamfer angle. The flank wear reached the minimum value for the tool with 0.18 mm chamfer width and 10° chamfer angle. The obtained composite model predicted good edge strength and minimum overall wear when the chamfer was 0.1 mm wide at a 10° angle. Thermal cracks were observed on the tools. They were small on the edges with the finest and least negative chamfer but were more significant on the more negative and greater chamfer. A great chamfer width and chamfer angle also resulted in insufficient chip evacuation. The results show how the edge geometry affects the tool’s reliability and wear and may help manufacturers minimize tool cost and downtime.

Optimization of Machining Parameters for Milling Zirconia Ceramics by Polycrystalline Diamond Tool

Zirconia ceramics are widely used in many fields because of their excellent physical and mechanical properties. However, there are some challenges to machine zirconia ceramics with high processing efficiency. In order to optimize parameters for milling zirconia ceramics by polycrystalline diamond tool, finite element method was used to simulate machining process based on Johnson-Cook constitutive model. The effects of spindle speed, feed rate, radial and axial cutting depth on cutting force, tool flank wear and material removal rate were investigated. The results of the simulation experiment were analyzed and optimized by the response surface method. The optimal parameter combination was obtained when the spindle speed, feed rate, radial and axial cutting depth were 8000 r/min, 90.65 mm/min, 0.10 mm and 1.37 mm, respectively. Under these conditions, the cutting force was 234.81 N, the tool flank wear was 33.40 μm when the milling length was 60 mm and the material removal rate was 44.65 mm3/min.

Application of AI techniques for modeling the performance measures in milling of 7075-T6 hybrid aluminum metal matrix composites

The prediction of performance measures is an essential one for manufacturers to increase the service life. This paper deals with the application of Artificial Intelligence (AI) to predict the performance measures like surface roughness, material removal rate, and flank wear during the milling process from the experimental data. The milling experiments were conducted in wet conditions based on the Response Surface Methodology (RSM) design of experiments. The spindle speed, feed rate, and axial depth of cut were considered as process parameters. The experimental data were used to develop the regression model, Mamdani fuzzy inference system, Backpropagation Neural Network (BPNN), and Adaptive Neuro-Fuzzy Inference System (ANFIS) model. The output of regression, fuzzy, neural network, and ANFIS model was compared with the experimental data, and predicted results were found to be in good conformity with the measured data. The prediction capability of the quadratic and Artificial Neural Network (ANN) model was very close to experimentally measured values and the quadratic model had an accuracy of 97.89% for surface roughness, 98.38% for material removal rate (MRR), and 95.72% for flank wear.

Investigation on surface roughness, tool wear and cutting power in MQL turning of bio-medical Ti-6Al-4V ELI alloy with sustainability

Ti-6Al-4V ELI (Grade 23) is highly recommended for bio-materials and due to its low thermal conductivity and chemically reactive properties, machinability is poor. Thus the current work emphasized on the selection of appropriate cooling technique and optimal cutting parameters for machining of Ti-6Al-4V ELI alloy with sustainability analysis for surface roughness, flank wear and cutting power. Initially, the cutting performances under dry, flood and MQL environments are compared and MQL is observed to better performed. At lower speed (70 m/min), MQL exhibited 26.38% and 19.69% lesser surface roughness relative to dry and flood cooling individually. At the same cutting condition, MQL assisted cutting resulted in lower flank wear relative to dry (157. 33%) and flood cooling (40%). Further, a detailed investigation has been made under MQL through Taguchi L18 design of experiments. The major mechanisms for flank wear are found to be abrasion, chipping and notch wear. Optimal data set through Grey relational analysis is found to be v1 (70 m/min), f1 (0.1 mm/rev) and d1 (0.1 mm) and improved. Quadratic regression model is found to be significant for prediction of responses. Sustainability Pugh matrix assessment revealed that MQL environment enhanced the economical, technological as well as environmental and operator health aspects. Reduction of energy consumption by 53.96% and savings of carbon footprints by 68.46 kg of CO2 observed under MQL at optimal conditions and thus saves manufacturing cost.

Development of multi sensor fusion based DAQ for in-process TCMS: Experimental and empirical analysis

In order to manufacture low-cost, high-quality goods, in-process tool condition monitoring is an essential responsibility in the manufacturing industry. In this study, a multisensor fusion technique was used to build and execute an effective and reliable TCM system in turning operations with coated and uncoated tungsten carbide inserts. In dry turning, an attempt has been made to optimize the turning process parameter and monitor the tool's condition. Acoustic optic emission based sensor i.e., Laser Doppler Vibrometer and FLIR E60 infrared thermal camera are strategically placed near the machining zone. Thermal images and vibration signals are recorded using an appropriate charge amplifier. To extract characteristics from numerous sensor data, a National Instruments data acquisition (NI-DAQ) system is constructed utilizing LabVIEW software. Thermal images are used to gather temperatures from tool-work piece locations. Vibration signals are translated into vibration parameters. These characteristics serve as the foundation for establishing in-process TCMS. Tool wear, vibrational displacements (Disp), and cutting temperature are investigated as a result of varied tool insert materials and process conditions (CT). Utilizing ISO 10816-3, ISO 3685, and ISO-18434-2008 standards, the cutting tool condition was assessed using extracted features from multi sensor fusion techniques. For Ti-6Al-4 V, the displacement of uncoated and coated tools increased by 65.28% and 44.71%, respectively. For AISI 316L flank wear, the uncoated insert effected 41% and the coated insert impacted 24.14%, respectively. While machining Al7075, the relationship of depth of cut and feed rate on flank wear maintains an identical trend. It is discovered that both temperature and displacement have a significant role in the evolution of flank wear, which is examined in depth. This paper recognizes the use of multi-sensor data in tool condition monitoring when rotating with various cutting tool inserts.

Turning of Inconel 718 Using Liquid Nitrogen: Multi-objective Optimization of Cutting Parameters Using RSM

The objective of this research was to investigate the effectiveness of application of liquid nitrogen (LN2) in turning of Inconel 718 compared to flooded cutting and select suitable LN2 cutting parameters using response surface methodology (RSM). The results of turning experiments conducted by spraying LN2 to the cutting area of Inconel 718 bar showed that using either low or high cutting parameters, cutting performance of Inconel 718 under the cryogenic condition was generally worse than the flooded cutting. However, using the medium cutting parameters the cutting performance was as good as flooded cutting showing the values of 90 N of cutting force, 60 µm of flank wear and 0.5-0.6 µm of surface roughness (Ra). These parameters were further optimized using desirability function of RSM to determine the set of parameters that provide the lowest cutting force, flank wear and Ra and the highest material removal rate (MRR) under cryogenic cutting. Analysis of variance (ANOVA) performed on the developed regression models showed that cutting speed was the significant factor on cutting force. Feed rate was the most influential parameter on flank wear. Feed rate and depth of cut was significant factors affecting Ra. Multi-objective optimization showed that a cutting speed of 87 m/min, a feed rate of 0.06 mm/rev and a depth of cut of 0.37 mm constituted the optimum cutting parameters for achieving the, cutting force of 78 N, flank wear of 58 µm, Ra of 0.49 µm and the MRR of 1.97 cm3/min under cryogenic cutting condition.

Fundamental Investigation into Tool Wear and Surface Quality in High-Speed Machining of Ti6Al4V Alloy

This paper reports a fundamental investigation consisting of systematic trials into the response of Ti6Al4V alloy to high-speed machining using carbide inserts. It is a useful extension to work previously published, and aims at assessing the impact of the process parameters, depth of cut, cutting speed and feed rate in addition to cutting length, and their interrelations, on observed crater and flank wear and roughness of the machined surface. The results showed that abrasion was the most important flank wear mechanism at high speed. It also showed that increased cutting length accelerated crater wear more than exhibited flank wear and had considerable effect on surface roughness. In particular, crater wear increased by over 150% (on average), and flank wear increased by 40% (on average) when increasing cutting length from 40 to 120 mm. However, cutting the same length increased surface roughness by 50%, which helps explain how progression of tool wear leads to deteriorated surface quality. ANOVA was used to perform statistical analyses of the measured data and revealed that cutting length and depth of cut had the greatest effect on both crater and flank wear of the cutting tool. These results confirm that high-speed machining of Ti6Al4V alloy is a reliable process, with cutting speed identified as having a relatively small influence on the tool wear and resultant roughness of the machined surface relative to other parameters.

IDENTIFICATION OF CHARACTER AND INTENSITY OF WEAR OF PVD COATED TWIST DRILLS IN DRILLING OF C 45 MATERIAL

This article is aimed to investigation of four different PVD coatings of STATON company in order to determine a wear behavior on twist drills when drilling C45 material. A pearlite-ferrite structure of C45 material is common material for automotive industry and highly abrasive to cutting tools. Our comparative study is focused on flank wear of the cutting wedge of observed drills deposited at STATON. The article shows differences in chemical composition and their effects on wear behavior at the corner of the drill and along the cutting edge. We also demonstrate that chemical composition has significant influence on the temperature of a build-up edge during cutting.

Wear Performance of The Zirconia Toughened Alumina Added With TiO2 and Cr2O3 Ceramic Cutting Tool

The zirconia toughened alumina enhanced with titania and chromia (ZTA-TiO2-Cr2O3) ceramic cutting tool is a new cutting tool that possesses good hardness and fracture toughness. However, the performance of the ZTA-TiO2-Cr2O3 cutting tool continues to remain unknown and therefore requires further study. In this research, the wearing of the ZTA-TiO2-Cr2O3 cutting tool and the surface roughness of the machined surface of stainless steel 316L was investigated. The experiments were conducted where the cutting speeds range between 314 to 455 m/min, a feed rate from 0.1 to 0.15 mm/rev, and a depth of cut of 0.2 mm. A CNC lathe machine was utilised to conduct the turning operation for the experiment. Additionally, analysis of the flank wear and crater wear was undertaken using an optical microscope, while the chipping area was observed via scanning electron microscopy (SEM). The surface roughness of the machined surface was measured via portable surface roughness. The lowest value of flank wear, crater wear and surface roughness obtained are 0.044 mm, 0.45 mm2, and 0.50 µm, respectively at the highest cutting speed of 455 m/min and the highest feed rate of 0.15 mm/rev. The chipping area became smaller with the increase of feed rate from 0.10 to 0.15 mm/rev and larger when the feed rate decrease. This was due to the reduced vibrations at the higher spindle speed resulting in a more stable cutting operation, thereby reducing the value of tool wear, surface roughness, and the chipping area.